Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: Shocks; Vortex ores; Regions of Recirculation; Boundary Layers; Wakes

Analysis of the Near-Wall Flow in a Turbine Cascade by Splat Visualization

Turbines are essential components of jet planes and power plants. Therefore, their efficiency and service life are of central engineering interest. In the case of jet planes or thermal power plants, the heating of the turbines due to the hot gas flow is critical. Besides effective cooling, it is a major goal of engineers to minimize heat transfer between gas flow and turbine by design. Since it is known that splat events have a substantial impact on the heat transfer between flow and immersed surfaces, we adapt a splat detection and visualization method to a turbine cascade simulation in this case study. Because splat events are small phenomena, we use a direct numerical simulation resolving the turbulence in the flow as the base of our analysis. The outcome shows promising insights into splat formation and its relation to vortex structures. This may lead to better turbine design in the future.Comment: Accepted at IEEE Scientific Visualization (SciVis) 2019. To appear in IEEE Transactions on Visualization and Computer Graphic

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction

Automatisation de la création de scénarios pour les scènes de la visualisation scientifique

RÉSUMÉ Bien que l’automatisation de la génération des chemins de caméra soit une pratique courante dans le cinéma et le jeu vidéo, elle fait preuve d’un retard important dans le milieu de la visualisation scientifique. La taille, la nature, la densité du maillage ainsi que l’absence de notions scénaristiques telles que les personnages et les actions font que l’opération d’import de règles de composition issues de domaines artistiques comme le cinéma ou la photographie ainsi que l’application des règles du montage deviennent plus complexe. Ce mémoire introduit une méthodologie qui propose une métamodélisation des attentes des scientifiques vis-à-vis de leurs données ainsi qu’une modélisation des comportements de données qui peuvent les intéresser. Ces modèles permettent de bâtir plus facilement des chemins de caméra pour des scènes numériques issues de simulations ou d’acquisitions. L’application des règles issues de la composition et du montage dans le but de produire des déplacements de caméra préservent l’intention du scientifique deviennent alors plus simple. La méthode a été expérimentée sur un ensemble de scènes issues de la mécanique des fluides et du génie biomédical; les résultats obtenus sur ces scènes nous ont permis de valider le fonctionnement de la méthodologie. Sont également proposés par la méthode un ensemble de paramètres de contrôle afin de modifier le processus de génération pour mieux l’adapter aux besoins précis que peut avoir un scientifique vis-à-vis d’une scène.----------ABSTRACT Automatic camera path generation is a common practice in film making and video games. However, it demonstrated a significant delay in scientific visualization due to the size, the nature, the mesh density and the lack of scriptwriting notions such as characters and actions. In this case, importing cinematography composition, photography composition and match cut rules becomes a more complex operation. This thesis presents a methodology that provides meta-models for the scientists' visualization expectations regarding their data and for the data behaviors that may interest them. These models make the camera paths generation process more intuitive. The application of composition and match cut rules, in order to produce camera moves that preserves the scientist's intention, becomes simpler. The method was tested on a set of scenes from fluid mechanics and biomedical engineering; the obtained results showed that our approach is a simple and efficient way for producing presentation videos. A set of control parameters are also provided by this method, in order to adapt the generation process to the specific needs that a scientist can have regarding his data

Vortex Extraction Of Vector Fields

Spinning, turbulent structures swirling around its centers within various flow media are known as vortices. The capability of locating and extracting vortical structures in flow data is crucial for understanding the flow. Vortices also have a strong impact on flow control and transport processes. Real-time vortex extraction methods are presented, offering immediate notion of the shape and location of the vortex structures. Using a real-time fluid simulation based on Navier-Stokes equations presented in \cite{Stam:1999:SF}, several vortex extraction methods are interactively performed in real-time. Following vortex extraction methods are implemented using the GPU: vorticity threshold, Q criterion, $\lambda_2$ criterion, the eigenvector method via parallel vectors operator (PVO) and the eigenvector method via coplanar vectors operator (CVO). Diffusional methods outputting flow fields with preserved/enhanced vortical structures are also presented. Such methods are useful for obtaining an alternative insight into vortices within a flow field and can also be used within the real-time simulation. Using a number of human performed gestures for human-computer interaction, special ensemble flow fields are produced. Detecting vortices from these gesture ensemble range flows is introduced as aid for gesture classification. Gesture range data is recorded using the Microsoft Kinect device. Range or scene flow is a 3D vector field describing movement within a scene. Range data consists of images (color channels) and corresponding depth images (depth channels) in which the distance of objects is recorded as a grayscale image. Ensemble range flow is estimated from gesture videos. Ensemble flow describes the overall flow within the scene and is obtained by averaging the structure tensor throughout the scene. Vortices are extracted from an ensemble range flow of the gestures. Their number and location is offering an additional parameter for gesture classification. Collection of methods for detecting vortices and obtaining vector fields with emphasized vortices are introduced in this thesis. Real-time execution of vortex extraction methods offers an instant notion of the nature of the flow. Diffusional methods can serve as a processing step within the real-time vortex extraction. As an additional application, gesture ensemble flow is presented. By detecting its vortices, a parameter for gesture classification is introduced

Effect of Forward Sweep on the Performance of an Axial Blower

Effects of changing the blade sweep without redesigning the datum blade sections are studied on the pressure rise, efficiency and 3D flow field of an axial blower. Four forward swept blade configurations (5°, 10°, 15° and 20°) are compared with an unswept blade. RANS and URANS simulations are carried out for the aerodynamic performance analysis and 3D flow field behaviour. Results indicated higher pressure rise and wider stall margin thus improved efficiency with higher forward sweep angles

Simulação numérica e visualização 3D interativa de objetos sob fluxos irrotacionais em tempo Quase-Real

Resumo: De uma maneira geral, qualquer fluxo irrotacional e incompressível é governado pela equação de Laplace. Esta não possui resolução analítica para problemas reais de engenharia, os quais possuem domínios e condições de contorno complexas, exceto para poucos casos particulares. A Dinâmica dos Fluidos Computacional (DFC) é um método utilizado para resolver numericamente a equação de Laplace, satisfazendo condições iniciais e de contorno. Porém, ao se refinar ou estender um domínio calculado, a quantidade de dados numéricos resultantes aumentará proporcionalmente e a análise destes valores pode se tornar complexa e onerosa. Complementariamente, para a compreensão dos resultados, é importante uma representação visual. A resolução numérica da equação de Laplace está descrita neste trabalho, com um algoritmo de solução inédito para as condições de contorno que atende qualquer forma geométrica em três dimensões. Desenvolveu-se um simulador que possibilita alterações geométricas de objetos 3D, calcula e visualiza interativamente velocidades, linhas de fluxo e força de sustentação para fluxos irrotacionais e incompressíveis em tempo quase-real. O sistema utiliza o método das diferenças finitas para a solução das equações. A interface gráfica foi desenvolvida utilizando, deste modo ineditamente para a DFC, a linguagem C++ e o VTK (Visualization Tool Kit). A quantidade, a origem das linhas de fluxo, a seleção do campo de velocidades, o cálculo da força de sustentação e a visualização estereoscópica são parâmetros que podem ser ajustados e selecionados para a visualização. O algoritmo passou por validações mostrando a capacidade de resolução em três dimensões. Assim, o simulador desenvolvido resolve, ao contrário dos softwares já existentes, o problema do cálculo e visualização interativa imediata ao se fazer modificações em objetos 3D. Este procedimento permitirá que se façam comparações entre formas geométricas imediatamente alteradas para que se possa escolher, entre elas, a que se adequar melhor às necessidades de um projeto